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System-Level Vulnerability Assessment for EME: From Fault Tree Analysis to Bayesian Networks—Part II: Illustration to Microcontroller System

机译:EME的系统级漏洞评估:从故障树分析到贝叶斯网络-第2部分:图示到微控制器系统

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摘要

The vulnerability of microcontroller system against high-altitude electromagnetic pulse (HEMP) is taken as an illustration to demonstrate the assessment methodology based on Bayesian networks (BN). The complete procedure is performed by two steps: the qualitative and the quantitative. The first step focuses on the analysis of three classes of properties, the electromagnetic environment, system function/structure, and their interactions. The primary BN model is built at the end of the first step. The second step investigates the BN nodes and branches one by one, which further implemented through two stages, i.e., the data acquisition and data fusion. The susceptibilities of devises are examined with the pulsed current injection. The responses of the transmission lines to HEMP are computed using the field-line coupling model. Comparing the probability density functions of the electromagnetic stresses and strengths produces the failure probabilities of the interface components. Through two-step analysis, the critical elements and coupling paths are identified and highlighted. After neglecting those unimportant factors, many BN nodes and branches are deleted. Thus, the complexity of assessment is reduced. By assigning the probability values to the simplified BN model, the system failure probability is calculated, which characterizes the system vulnerability against HEMP environment. The illustration validates the rationality and flexibility of the BN assessment methodology.
机译:以微控制器系统对高海拔电磁脉冲(HEMP)的脆弱性为例,说明了基于贝叶斯网络(BN)的评估方法。完整的过程分为两个步骤:定性和定量。第一步着重分析三类属性,电磁环境,系统功能/结构及其相互作用。第一步结束时将建立主要的BN模型。第二步研究BN节点并一个接一个地分支,进一步通过两个阶段即数据采集和数据融合来实现。用脉冲电流注入检查装置的敏感性。使用场线耦合模型来计算传输线对HEMP的响应。比较电磁应力和强度的概率密度函数会产生界面组件的失效概率。通过两步分析,可以识别并突出显示关键元素和耦合路径。在忽略了那些不重要的因素之后,许多BN节点和分支被删除。因此,降低了评估的复杂性。通过将概率值分配给简化的BN模型,可以计算出系统故障概率,该概率表征了针对HEMP环境的系统漏洞。该图验证了BN评估方法的合理性和灵活性。

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